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                <div id="site-name"><a href="../../sphinx_pages/build/html/index.html">Shark machine learning library</a></div>
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<div class="textblock">Here is a list of all functions with links to the classes they belong to:</div>

<h3><a id="index_c" name="index_c"></a>- c -</h3><ul>
<li>C()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_linear_svm_trainer.html#ac310ca5530798f1190130d8495dd2f07">shark::AbstractLinearSvmTrainer&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_abstract_svm_trainer.html#a7bc3baa63458c785155a231ca73ea483">shark::AbstractSvmTrainer&lt; InputType, LabelType, Model, Trainer &gt;</a>, <a class="el" href="classshark_1_1_kernel_budgeted_s_g_d_trainer.html#a55681941faf8293971193dce813c5651">shark::KernelBudgetedSGDTrainer&lt; InputType, CacheType &gt;</a>, <a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html#a442f481e2e8f97156994ed478ec5d91f">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a></li>
<li>cachedLines()&#160;:&#160;<a class="el" href="classshark_1_1_l_r_u_cache.html#a02ecc15b8471e026cfe4a5f93bf66b49">shark::LRUCache&lt; T &gt;</a></li>
<li>CachedMatrix()&#160;:&#160;<a class="el" href="classshark_1_1_cached_matrix.html#acbf86b7470e20b4176d2ec56c6be2c8a">shark::CachedMatrix&lt; Matrix &gt;</a></li>
<li>cacheSize()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_svm_trainer.html#a954cc587b52b4ec5a347134804dfc812">shark::AbstractSvmTrainer&lt; InputType, LabelType, Model, Trainer &gt;</a>, <a class="el" href="classshark_1_1_kernel_s_g_d_trainer.html#ac0183963a7f82e77ba7333666e05f895">shark::KernelSGDTrainer&lt; InputType, CacheType &gt;</a></li>
<li>CacheSize()&#160;:&#160;<a class="el" href="classshark_1_1_one_class_svm_trainer.html#aba568782c774e6460d3fc160b01fd94b">shark::OneClassSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>calcGradient()&#160;:&#160;<a class="el" href="classshark_1_1_qp_mc_linear.html#a6ff5650431f4502b6a76e7b79b7ff514">shark::QpMcLinear&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_a_d_m.html#af8021dbbe5f3c4b3e5fdc83b941748cd">shark::QpMcLinearADM&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_a_t_m.html#afe91c0937cc28462d3d6d6dbeca8a52d">shark::QpMcLinearATM&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_a_t_s.html#aa878c63a7b0758bc2ad71d77bc65975f">shark::QpMcLinearATS&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_c_s.html#a800c787ffc88f44571a67e66f83d9f2b">shark::QpMcLinearCS&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_l_l_w.html#a5d36501d3f63730064d4439657bcb21f">shark::QpMcLinearLLW&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_m_m_r.html#a63cf5cf3a2059c597bc266cc4cd35674">shark::QpMcLinearMMR&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_reinforced.html#ab3ba8e3be351d681e3bbba6da830d6a3">shark::QpMcLinearReinforced&lt; InputT &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_linear_w_w.html#a229d689f6acbd6074b047fea92f90ce3">shark::QpMcLinearWW&lt; InputT &gt;</a></li>
<li>calculateCuttingDimension()&#160;:&#160;<a class="el" href="classshark_1_1_k_d_tree.html#a7d49ee634a593c727aa4896c4d0683fc">shark::KDTree&lt; InputT &gt;</a></li>
<li>calculateEnergy()&#160;:&#160;<a class="el" href="classshark_1_1_gibbs_operator.html#a8ba4607be52c15e7e69f8c10fa9ccf65">shark::GibbsOperator&lt; RBMType &gt;</a></li>
<li>calculateNormal()&#160;:&#160;<a class="el" href="classshark_1_1_k_h_c_tree.html#a3af2b2683dfe8b119f248e54c1c5d044">shark::KHCTree&lt; Container, CuttingAccuracy &gt;</a>, <a class="el" href="classshark_1_1_l_c_tree.html#a254750fdf8053dfeead8442b783caba8">shark::LCTree&lt; VectorType, CuttingAccuracy &gt;</a></li>
<li>canGenerateRandomPoint()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_constraint_handler.html#a454524f3253a60a2564a21045fbdc5e9">shark::AbstractConstraintHandler&lt; SearchPointType &gt;</a></li>
<li>canProposeStartingPoint()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_objective_function.html#aa190c3699e653df3f054b0b3d753270e">shark::AbstractObjectiveFunction&lt; PointType, ResultT &gt;</a></li>
<li>canProvideClosestFeasible()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_constraint_handler.html#a05adea67dd581616abf51b9f51d425c9">shark::AbstractConstraintHandler&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_abstract_objective_function.html#a499c48a9afe9e77e866af66c0cb4f396">shark::AbstractObjectiveFunction&lt; PointType, ResultT &gt;</a></li>
<li>canSolveConstrained()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_optimizer.html#aecad1d60d38fd243eaf7c7bf0f6d01af">shark::AbstractOptimizer&lt; PointType, ResultT, SolutionTypeT &gt;</a></li>
<li>cardP()&#160;:&#160;<a class="el" href="classshark_1_1_qp_mc_box_decomp.html#a1f350d9542e7f74116f37648d5a2e582">shark::QpMcBoxDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#a7d1d145388dafe52b13d4537c185df9c">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a></li>
<li>CARTree()&#160;:&#160;<a class="el" href="classshark_1_1_c_a_r_tree.html#a81e32e481410512f89d6ce6f6cd7dc35">shark::CARTree&lt; LabelType &gt;</a></li>
<li>centers()&#160;:&#160;<a class="el" href="classshark_1_1_r_b_f_layer.html#ad8f489205e3fb40eb807298df0c4819a">shark::RBFLayer</a></li>
<li>centroids()&#160;:&#160;<a class="el" href="classshark_1_1_centroids.html#a8dcfd9a069a3ea8456e126138f3dee37">shark::Centroids</a></li>
<li>Centroids()&#160;:&#160;<a class="el" href="classshark_1_1_centroids.html#ab83a899ae20f7e40bfbe6e84688b9401">shark::Centroids</a></li>
<li>chain()&#160;:&#160;<a class="el" href="classshark_1_1_multi_chain_approximator.html#a2399386f6eb6a5b3fc39197f1e147440">shark::MultiChainApproximator&lt; MarkovChainType &gt;</a>, <a class="el" href="classshark_1_1_single_chain_approximator.html#a62326355cc08502f382293d242e14e65">shark::SingleChainApproximator&lt; MarkovChainType &gt;</a></li>
<li>checkFeatures()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_optimizer.html#ae7a23300641448c761b6aa0305b7ef66">shark::AbstractOptimizer&lt; PointType, ResultT, SolutionTypeT &gt;</a></li>
<li>checkKKT()&#160;:&#160;<a class="el" href="classshark_1_1_box_constrained_problem.html#af60ac2b478f7a141fca100daa8217edd">shark::BoxConstrainedProblem&lt; SVMProblem &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_box_decomp.html#a0aa24d59eb4a98a8fcc5c9c37d03d3b5">shark::QpMcBoxDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_qp_mc_simplex_decomp.html#a62b40d1335f1aa500d790cf6b5e0d735">shark::QpMcSimplexDecomp&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_svm_problem.html#a33eaf27af1bb982dcd7f965fcfbce884">shark::SvmProblem&lt; Problem &gt;</a></li>
<li>Chessboard()&#160;:&#160;<a class="el" href="classshark_1_1_chessboard.html#ab98d4611c8a5c73da99449bd89711b36">shark::Chessboard</a></li>
<li>chromosome()&#160;:&#160;<a class="el" href="classshark_1_1_individual.html#addfc461c9e7394ee238e6f5c18537646">shark::Individual&lt; PointType, FitnessTypeT, Chromosome &gt;</a></li>
<li>Cigar()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_cigar.html#ac25b515e63e4a24272167417bce5c9af">shark::benchmarks::Cigar</a></li>
<li>CigarDiscus()&#160;:&#160;<a class="el" href="classshark_1_1benchmarks_1_1_cigar_discus.html#a19caaa6a1eb8f079afe5d78d88543f2c">shark::benchmarks::CigarDiscus</a></li>
<li>CIGTAB1()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_c_i_g_t_a_b1.html#a62c45d636c14e296c4f6827f767415cf">shark::benchmarks::CIGTAB1</a></li>
<li>CIGTAB2()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_c_i_g_t_a_b2.html#a378f97988070d1eb7a190f29eac23466">shark::benchmarks::CIGTAB2</a></li>
<li>CircleInSquare()&#160;:&#160;<a class="el" href="classshark_1_1_circle_in_square.html#a75c2e5aa442b209a3658ef8cb0389508">shark::CircleInSquare</a></li>
<li>Classifier()&#160;:&#160;<a class="el" href="classshark_1_1_classifier.html#acca41eec396129e8c9859d1115d2bb65">shark::Classifier&lt; Model &gt;</a></li>
<li>clear()&#160;:&#160;<a class="el" href="classshark_1_1_cached_matrix.html#ae000f8c2a306080058593b6ade36db12">shark::CachedMatrix&lt; Matrix &gt;</a>, <a class="el" href="classshark_1_1_l_r_u_cache.html#afd6ed6c3442f200616f4c7d4cee32144">shark::LRUCache&lt; T &gt;</a>, <a class="el" href="classshark_1_1_precomputed_matrix.html#a84e83ea244a5ae6d7c3881a653541ee3">shark::PrecomputedMatrix&lt; Matrix &gt;</a></li>
<li>clearModels()&#160;:&#160;<a class="el" href="classshark_1_1_ensemble.html#ab04ccf3f9acb405f3fdedd125ff5ed1c">shark::Ensemble&lt; ModelType, OutputType &gt;</a></li>
<li>closestFeasible()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_constraint_handler.html#abb58033fab48e9ffd58021054f916c7f">shark::AbstractConstraintHandler&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_abstract_objective_function.html#a68b3dfe1642e13693b5ab610f3fc5f79">shark::AbstractObjectiveFunction&lt; PointType, ResultT &gt;</a>, <a class="el" href="classshark_1_1_box_constraint_handler.html#a791747463fd86c8988f4caafda3b6e55">shark::BoxConstraintHandler&lt; Vector &gt;</a>, <a class="el" href="classshark_1_1_evaluation_archive.html#aa9db8a8ad6cdd5b53cb03966c7ad03a8">shark::EvaluationArchive&lt; PointType, ResultT &gt;</a></li>
<li>ClusteringModel()&#160;:&#160;<a class="el" href="classshark_1_1_clustering_model.html#aa40b5785d0746a501fbeea70510eb59c">shark::ClusteringModel&lt; InputT, OutputT &gt;</a></li>
<li>CMA()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#a87ad8d08471b5488311a53c5f0a07594">shark::CMA</a></li>
<li>CMAChromosome()&#160;:&#160;<a class="el" href="structshark_1_1_c_m_a_chromosome.html#a3140075b6f17139924e0a45a3f0270b9">shark::CMAChromosome</a></li>
<li>CMACMap()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a_c_map.html#ab3c645c7695685c7f79a4bbbf1eb3f9a">shark::CMACMap</a></li>
<li>CMAIndividual()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a_individual.html#ae272f1d52554bfda48aea84ee864eb07">shark::CMAIndividual&lt; FitnessType &gt;</a></li>
<li>CMSA()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_s_a.html#ac4578fae098a5b45e7f301a2693490d0">shark::CMSA</a></li>
<li>CombinedObjectiveFunction()&#160;:&#160;<a class="el" href="classshark_1_1_combined_objective_function.html#a435fd031ee3d4c3a21b68d843df24694">shark::CombinedObjectiveFunction&lt; SearchPointType, ResultT &gt;</a></li>
<li>computeFeatureImportances()&#160;:&#160;<a class="el" href="classshark_1_1_r_f_classifier.html#a290cb9386878b0264faf15dae5dc2068">shark::RFClassifier&lt; LabelType &gt;</a></li>
<li>computeMatrix()&#160;:&#160;<a class="el" href="classshark_1_1_gaussian_task_kernel.html#aefbd61ad0c2f8c4adb06669bd49a41f1">shark::GaussianTaskKernel&lt; InputTypeT &gt;</a></li>
<li>computeNorm()&#160;:&#160;<a class="el" href="classshark_1_1_missing_features_kernel_expansion.html#ad2194899bc2ad060c751e6f15dceb91a">shark::MissingFeaturesKernelExpansion&lt; InputType &gt;</a></li>
<li>computeOOBerror()&#160;:&#160;<a class="el" href="classshark_1_1_r_f_classifier.html#a336a6c2b13f973dd780644319dab4e8a">shark::RFClassifier&lt; LabelType &gt;</a></li>
<li>computeRadiusMargin()&#160;:&#160;<a class="el" href="classshark_1_1_radius_margin_quotient.html#a72f6cfe0cc96c2f1551861af80323f47">shark::RadiusMarginQuotient&lt; InputType, CacheType &gt;</a></li>
<li>computeSearchDirection()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_line_search_optimizer.html#a042c4dddbfd3bf00c981e66bd363d6db">shark::AbstractLineSearchOptimizer&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_b_f_g_s.html#a9b943472e508d91139ba51a02faeed3e">shark::BFGS&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_c_g.html#a971b91d5b0e5bd780a12e82b54be4dc7">shark::CG&lt; SearchPointType &gt;</a>, <a class="el" href="classshark_1_1_l_b_f_g_s.html#a2cf819c6eb6e886395ae71df403edc6e">shark::LBFGS&lt; SearchPointType &gt;</a></li>
<li>computeTrellis()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_calculator_m_d_h_o_y.html#affaeb9fcc85d387adb0dd5eb45949c01">shark::HypervolumeCalculatorMDHOY</a></li>
<li>condition()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#a7a80596955e5d064cc8e6f2a69498c5e">shark::CMA</a></li>
<li>configure()&#160;:&#160;<a class="el" href="classshark_1_1_grid_search.html#abb3472e263958e425bb45b3556d52e7c">shark::GridSearch</a>, <a class="el" href="classshark_1_1_nested_grid_search.html#a6794001d6de702afc1cb5eb323e1335b">shark::NestedGridSearch</a>, <a class="el" href="classshark_1_1_point_search.html#a17f57ad1f208eb3d036b083fafd0180c">shark::PointSearch</a></li>
<li>ConstantNoise()&#160;:&#160;<a class="el" href="classshark_1_1_cross_entropy_method_1_1_constant_noise.html#a0af64a18dea0a2cbeb8a281ad4e6ba64">shark::CrossEntropyMethod::ConstantNoise</a></li>
<li>constrainedPenaltyFactor()&#160;:&#160;<a class="el" href="classshark_1_1_elitist_c_m_a.html#a415fd8e3a2a3698628e7cbe3bdea0ad4">shark::ElitistCMA</a></li>
<li>ConstrainedSphere()&#160;:&#160;<a class="el" href="structshark_1_1benchmarks_1_1_constrained_sphere.html#a802dfd1afeeb99fca85c9786772540fc">shark::benchmarks::ConstrainedSphere</a></li>
<li>containsBoundary()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_calculator_m_d_h_o_y.html#a53fe5df7055cd030bd15ab8ea7200820">shark::HypervolumeCalculatorMDHOY</a></li>
<li>ContrastiveDivergence()&#160;:&#160;<a class="el" href="classshark_1_1_contrastive_divergence.html#a7b5c3fb150a0a986990ef1a5ce80c870">shark::ContrastiveDivergence&lt; Operator &gt;</a></li>
<li>Conv2DModel()&#160;:&#160;<a class="el" href="classshark_1_1_conv2_d_model.html#a6ca37037a3ff8605a970d45ecad0090b">shark::Conv2DModel&lt; VectorType, ActivationFunction &gt;</a></li>
<li>cosAngles()&#160;:&#160;<a class="el" href="structshark_1_1_reference_vector_guided_selection.html#aef0dbf448c9f01c70eb7defccabdd58b">shark::ReferenceVectorGuidedSelection&lt; IndividualType &gt;</a></li>
<li>countAttributes()&#160;:&#160;<a class="el" href="classshark_1_1_c_a_r_tree.html#ac18ee6d585b246bbd221c08639a0cef0">shark::CARTree&lt; LabelType &gt;</a>, <a class="el" href="classshark_1_1_r_f_classifier.html#a6cc321d1bcb9c18ba50857d093063730">shark::RFClassifier&lt; LabelType &gt;</a></li>
<li>covarianceMatrix()&#160;:&#160;<a class="el" href="classshark_1_1_c_m_a.html#a2fe67c78f272defd3e468d0eeaa1a553">shark::CMA</a>, <a class="el" href="classshark_1_1_multi_variate_normal_distribution.html#ab2f0af22ae2978225f6990f2abc01079">shark::MultiVariateNormalDistribution</a></li>
<li>covers()&#160;:&#160;<a class="el" href="structshark_1_1_hypervolume_calculator_m_d_h_o_y.html#a36ffa75e34e89103448a624928942dfc">shark::HypervolumeCalculatorMDHOY</a></li>
<li>createBatch()&#160;:&#160;<a class="el" href="structshark_1_1_batch_3_01shark_1_1blas_1_1compressed__vector_3_01_t_01_4_01_4.html#a7d807af16dbda22f9fa7efa6a8222843">shark::Batch&lt; shark::blas::compressed_vector&lt; T &gt; &gt;</a></li>
<li>createBatchFromRange()&#160;:&#160;<a class="el" href="structshark_1_1_batch_3_01shark_1_1blas_1_1compressed__vector_3_01_t_01_4_01_4.html#a5eab4ea5b33cefa429ba70a9dc852eb5">shark::Batch&lt; shark::blas::compressed_vector&lt; T &gt; &gt;</a></li>
<li>createRoot()&#160;:&#160;<a class="el" href="classshark_1_1_c_a_r_tree.html#ad91c08d09c8d94522cb44b7807a73ade">shark::CARTree&lt; LabelType &gt;</a></li>
<li>createSample()&#160;:&#160;<a class="el" href="classshark_1_1_gibbs_operator.html#a6cf9658a4eb72ac3dc3dbaa44a51c726">shark::GibbsOperator&lt; RBMType &gt;</a></li>
<li>createState()&#160;:&#160;<a class="el" href="classshark_1_1_abstract_kernel_function.html#a9057a4a71b4d28febb171e09bbd22c07">shark::AbstractKernelFunction&lt; InputTypeT &gt;</a>, <a class="el" href="classshark_1_1_abstract_model.html#a47d80a74ce80e5dd5e2851c52738b86b">shark::AbstractModel&lt; InputTypeT, OutputTypeT, ParameterVectorType &gt;</a>, <a class="el" href="classshark_1_1_a_r_d_kernel_unconstrained.html#a756d97810b5d84179e102200c433a13e">shark::ARDKernelUnconstrained&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_c_a_r_tree.html#ab61230bfb1fa0dabe95576205b9dfdfc">shark::CARTree&lt; LabelType &gt;</a>, <a class="el" href="classshark_1_1_c_m_a_c_map.html#a262bfb0a301de3af1bcac7f5718ef782">shark::CMACMap</a>, <a class="el" href="classshark_1_1_concatenated_model.html#ac474247bfc1639fe5aea49156a9b608d">shark::ConcatenatedModel&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_conv2_d_model.html#aa837cb1b2e7f96cee6384c1464ad0bfb">shark::Conv2DModel&lt; VectorType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_discrete_kernel.html#ac4ad2a25a3846fc24daa142790d15e67">shark::DiscreteKernel</a>, <a class="el" href="classshark_1_1_dropout_layer.html#a91e4f300eb52f22ca8a39c8c6b26f039">shark::DropoutLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_gaussian_rbf_kernel.html#a5104097639bdf4b8105c548144e87e50">shark::GaussianRbfKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_kernel_expansion.html#ae4764c8830fd7f7b65e43e3e4210dba1">shark::KernelExpansion&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_linear_kernel.html#ac46b5d8fa1d529a9b91b1f7a139454f6">shark::LinearKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_linear_model.html#aa24c6a19288e028495d0bef6f55f8131">shark::LinearModel&lt; InputType, ActivationFunction &gt;</a>, <a class="el" href="classshark_1_1_missing_features_kernel_expansion.html#abccbbad9f32c73e2419bc120c5ebb53c">shark::MissingFeaturesKernelExpansion&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_model_kernel.html#a3608a4bdd1288a8a96a323995a5cb261">shark::ModelKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_monomial_kernel.html#a2f49cf121f768ed37f5c945ebe80a279">shark::MonomialKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_neuron_layer.html#acc42a1d34884effef8d1598aa35ab5a2">shark::NeuronLayer&lt; NeuronType, VectorType &gt;</a>, <a class="el" href="classshark_1_1_normalized_kernel.html#aa438ef5e9b9e54da9ba0de32ee02666b">shark::NormalizedKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_normalizer.html#af23981098d22aa69fcf0b258efae50e8">shark::Normalizer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_one_versus_one_classifier.html#a24d1e801c037be39351c83f7c102bdc2">shark::OneVersusOneClassifier&lt; InputType, VectorType &gt;</a>, <a class="el" href="classshark_1_1_point_set_kernel.html#add8df8653ba9dd2adfcaac7e5c44afac">shark::PointSetKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_polynomial_kernel.html#a6e19c738faff1a554846ece7327abb70">shark::PolynomialKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_pooling_layer.html#aefd4642921dff88b3f8ecde017be2698">shark::PoolingLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_r_b_f_layer.html#a3193c0bff83fdf1e5ed37f12d9639351">shark::RBFLayer</a>, <a class="el" href="classshark_1_1_r_b_m.html#a5e0f8d86ec292aeb2cd89525750a5079">shark::RBM&lt; VisibleLayerT, HiddenLayerT, randomT &gt;</a>, <a class="el" href="classshark_1_1_resize_layer.html#a997263b15ab2384f4d2b3006caf32211">shark::ResizeLayer&lt; VectorType &gt;</a>, <a class="el" href="classshark_1_1_scaled_kernel.html#a8ea7e45b7d287c3e15968937c5076d17">shark::ScaledKernel&lt; InputType &gt;</a>, <a class="el" href="classshark_1_1_weighted_sum_kernel.html#a8f5c7a811096153b2cc2add881ea3b41">shark::WeightedSumKernel&lt; InputType &gt;</a></li>
<li>CrossEntropy()&#160;:&#160;<a class="el" href="classshark_1_1_cross_entropy_3_01blas_1_1vector_3_01_t_00_01_device_01_4_00_01blas_1_1vector_3_01_t_00_01_device_01_4_01_4.html#ab8d138b1cecc664543c1b00f07a2d492">shark::CrossEntropy&lt; blas::vector&lt; T, Device &gt;, blas::vector&lt; T, Device &gt; &gt;</a>, <a class="el" href="classshark_1_1_cross_entropy_3_01unsigned_01int_00_01_output_type_01_4.html#ab3f85fac7c5cb438eeecd05d4e6a07db">shark::CrossEntropy&lt; unsigned int, OutputType &gt;</a></li>
<li>CrossEntropyMethod()&#160;:&#160;<a class="el" href="classshark_1_1_cross_entropy_method.html#a6cbaa9d9b87109f7616bead343cf3a93">shark::CrossEntropyMethod</a></li>
<li>crossoverProbability()&#160;:&#160;<a class="el" href="classshark_1_1_indicator_based_real_coded_n_s_g_a_i_i.html#afa51910d25d0109c4da7b662bccb4064">shark::IndicatorBasedRealCodedNSGAII&lt; Indicator &gt;</a>, <a class="el" href="classshark_1_1_m_o_e_a_d.html#a31e982735b8a679e0deec45afe631141">shark::MOEAD</a>, <a class="el" href="classshark_1_1_r_v_e_a.html#a24e4f06d4e80c60c5d5c808aca9441c5">shark::RVEA</a>, <a class="el" href="classshark_1_1_s_m_s_e_m_o_a.html#a3e3aa4a746555fd8305b86140b32701a">shark::SMSEMOA</a></li>
<li>CrossValidationError()&#160;:&#160;<a class="el" href="classshark_1_1_cross_validation_error.html#a8b8619981a0a2a7d041d367d28d212f3">shark::CrossValidationError&lt; ModelTypeT, LabelTypeT &gt;</a></li>
<li>CSvmDerivative()&#160;:&#160;<a class="el" href="classshark_1_1_c_svm_derivative.html#a7ee628c62b706b9b7439840ae5a9546d">shark::CSvmDerivative&lt; InputType, CacheType &gt;</a></li>
<li>CSVMProblem()&#160;:&#160;<a class="el" href="classshark_1_1_c_s_v_m_problem.html#a24063221b317718fb10aa445b2fc8d76">shark::CSVMProblem&lt; MatrixT &gt;</a></li>
<li>CSvmTrainer()&#160;:&#160;<a class="el" href="classshark_1_1_c_svm_trainer.html#ab9e81925c8a8a25db71614edcae230f0">shark::CSvmTrainer&lt; InputType, CacheType &gt;</a></li>
<li>CVFolds()&#160;:&#160;<a class="el" href="classshark_1_1_c_v_folds.html#ad1e48f9176458dbb2d1229219baafbed">shark::CVFolds&lt; DatasetTypeT &gt;</a></li>
</ul>
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